In this blog post I want to introduce new statistics and analysis capabilities for Data Actions in SAP Analytics Cloud.
The goal is to enable the user to:
- get an overview of the Data Actions
- see statistics, detect patterns and trends in the execution history
- analyse single Data Actions that have been triggered
When and Where do I get it?
With Wave 2021.07 and 2021.Q2 QRC Release the Story Data Action Performance Statistics and Analysis and the underlying Live Model PLANNING_DATA_ACTIONS will be released.
Data Action Performance Statistics and Analysis will be deployed automatically under the System Directory into the folder SAC Content which is already known from previous shipments of SAP Analytics Cloud Performance Statistics and Analysis. In case you need more details on how to find the content please visit the “Where can I get it?” Section of SAP Analytics Cloud Performance Analysis Tool.
How can I use it and what information can I access?
Once you open the Story Data Action Performance Statistics and Analysis, the Overview page will open.
The Overview page can be distributed into two sections. On one hand on top of the page the filter bar and on the other hand below it, the KPI section.
In the filter section you can limit the KPI section to a timeframe and a specific Model that you are interested in or get the full picture.
Data Action KPIs
The KPI section shows 6 Numeric Point Charts with variance values for the previous period for each KPI.
The first points the number of users that either have scheduled a Data Action or directly triggered one from within a Story or Analytic Application.
The second chart shows the number of Models that have been accessed by Data Actions.
The third chart indicates the number of Data Actions that have been triggered whereas the fourth charts shows how often those Data Actions have been executed.
The fifth and sixth charts show how many of these executions have been scheduled via from a calendar task or from a Story or Analytic Application within the selected timeframe.
Below this information we show three top 5 “Data Action/ Model – Combinations” rankings for the following criteria:
- Median Duration to complete [ms]
- Number of Executions
- Number of Failures
Statistics and Analysis
The second page focuses on Data Action statistics and analysis.
The page is structured into four sections. First we have a KPI section, followed by a Time Series Chart that can be used to filter the table below which lists the data actions per date and can be used to filter further down to a single data action on a specific date. The different status and steps of single entries can then be analysed.
The data can be limited by Date, Data Action, Model Name, User Name, the Story or Analytic Application where the Data Action has been triggered from and whether the Data Action has been scheduled by a calendar task or by Story or Analytic Application.
The Data Action KPIs show the average and maximum number of executions, the median and maximum duration, and the amount of successful and failed executions for the selection.
Execution Count and Maximum Data Action Count
The time series chart shows the execution count and maximum Data Action duration in milliseconds for the selection.
This chart can be used to filter the tables below for a specific date which results in a table view that shows the date and time when the Data Action has been triggered, its final status and the name of the Data Action and the Model that has been used. In addition we show the number of steps of the Data Action, the name of the Story, Analytic Application or Calendar Task that it has been triggered from as well as the type of the same and the full duration of the Data Action in milliseconds.
Data Action Statistics and Analysis
Once you have selected a single entry, you want to analyse, the two tables at the bottom of the page refresh for detailed analysis of the Data Action.
The left table shows the status and step overview with each step’s timestamp whereas the right table shows the duration for each of the steps. This helps to understand whether the Data Action was waiting to be processed, whether a specific step during the processing was problematic, etc.
- Statistics for Versions on Planning Models